WhatsApp AI Support Automation Integration
Budget: ₹1,500 – ₹12,500 INR
I want to turn my WhatsApp Cloud API number into a fully-featured, AI-driven customer service channel. The goal is simple: automate repetitive support tasks while still giving customers a smooth, natural chat experience.
Here’s what the system must do:
• Run a chatbot that answers everyday FAQs in real time, pulling from a knowledge base I can update easily.
• Detect customer sentiment on each incoming message so we can prioritise unhappy users and escalate when necessary.
• Send automated follow-up responses (e.g., “Is everything resolved?”) after configurable time windows.
• Create formal quotations inside the chat, convert them to bills/invoices, and deliver the PDF or link back to the customer.
• Guide users through form-filling steps, validating their inputs before submission.
Technical notes
The solution needs to plug directly into the WhatsApp Cloud API webhook. I’m comfortable with Python, Node.js or a similar stack—use whatever best supports NLP models and quick deployment. Please ensure the code is modular (separate logic for NLP, billing, and webhook handling) and ready for containerised hosting.
Deliverables
1. Source code with clear README and environment variables for the WhatsApp Cloud API credentials.
2. Trained or configurable AI models/scripts covering FAQ answers, sentiment scoring, and follow-ups.
3. Quotation, billing and form-helper modules with sample templates.
4. Deployment guide (Docker or similar) plus a brief video or live demo showing the workflow from user message to automated response.
Acceptance criteria
• All listed features work end-to-end in a test WhatsApp Cloud API sandbox.
• Latency below two seconds for standard replies.
• Sentiment labels reach at least 80 % accuracy on my test set.
• Code passes a quick security review—no hard-coded keys, no exposed endpoints.
Once these points are met, we can push straight to production. Looking forward to seeing how you’d structure the build.
Here’s what the system must do:
• Run a chatbot that answers everyday FAQs in real time, pulling from a knowledge base I can update easily.
• Detect customer sentiment on each incoming message so we can prioritise unhappy users and escalate when necessary.
• Send automated follow-up responses (e.g., “Is everything resolved?”) after configurable time windows.
• Create formal quotations inside the chat, convert them to bills/invoices, and deliver the PDF or link back to the customer.
• Guide users through form-filling steps, validating their inputs before submission.
Technical notes
The solution needs to plug directly into the WhatsApp Cloud API webhook. I’m comfortable with Python, Node.js or a similar stack—use whatever best supports NLP models and quick deployment. Please ensure the code is modular (separate logic for NLP, billing, and webhook handling) and ready for containerised hosting.
Deliverables
1. Source code with clear README and environment variables for the WhatsApp Cloud API credentials.
2. Trained or configurable AI models/scripts covering FAQ answers, sentiment scoring, and follow-ups.
3. Quotation, billing and form-helper modules with sample templates.
4. Deployment guide (Docker or similar) plus a brief video or live demo showing the workflow from user message to automated response.
Acceptance criteria
• All listed features work end-to-end in a test WhatsApp Cloud API sandbox.
• Latency below two seconds for standard replies.
• Sentiment labels reach at least 80 % accuracy on my test set.
• Code passes a quick security review—no hard-coded keys, no exposed endpoints.
Once these points are met, we can push straight to production. Looking forward to seeing how you’d structure the build.